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Glama

Find brands

kh_brands
Read-onlyIdempotent

Search and list brands by name in Persian or English, returning slugs for use with browse and filter tools. Supports pagination and A-Z listing.

Instructions

Find brands by name (about 3,200) with their slugs, for the brands of kh_browse / kh_filters.

Input Schema

NameRequiredDescriptionDefault
pageNoPage number, from 1.
limitNoBrands per page.
queryNoBrand name, Persian or English, e.g. 'سیمپل' or 'cerave'. Empty = all, A-Z.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.2.0
    • changedInput schema / properties / limit / default
      Previous value: -50New value: +30
    • removedInput schema / properties / limit / title
      Removed value: -"Limit"
    • removedInput schema / properties / page / title
      Removed value: -"Page"
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / title
      Removed value: -"kh_brandsArguments"
    • changedOutput schema / (root)
      Previous value: -{
      -  "additionalProperties": true,
      -  "title": "kh_brandsDictOutput",
      -  "type": "object"
      -}New value: +null
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety/idempotency are covered. The description adds the corpus size and that slugs are returned, but says nothing about pagination behavior or result ordering beyond what annotations and schema imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence opening with the verb; the parenthetical count and the downstream-tool note are both informative and earn their place. No filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a non-destructive paginated lookup with full schema coverage and comprehensive annotations, the description covers what is returned (brands + slugs) and the dataset scale. It could be slightly more complete by noting the paginated list shape, since there is no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so page/limit/query are fully documented in the schema (including Persian/English examples and empty = all, A-Z). The description's 'by name' adds no syntax or format detail beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Find brands') with useful qualifiers: the dataset size (~3,200), the return payload (slugs), and the downstream consumers (kh_browse / kh_filters). It does not explicitly contrast itself with lookups like kh_categories or kh_search, so sibling differentiation is implied rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear context of use by naming the tools whose `brands` filter this feeds (kh_browse, kh_filters), which tells an agent why to call it. It stops short of explicit when-not rules or naming an alternative lookup tool for the same need.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.